2008/02/05 by Stefan Lämmer, Dirk Helbing · 341 citations
Engineering · Physics and Astronomy · Social Sciences · #Anticipation (artificial intelligence) #Artificial intelligence #Computer network #Computer science #Control (management) #Distributed computing #Engineering #Evacuation and Crowd Dynamics #Floating car data #Queue #Service (business) #Simulation #Traffic bottleneck #Traffic congestion #Traffic congestion reconstruction with Kerner's three-phase theory #Traffic control and management #Traffic flow (computer networking) #Traffic optimization #Traffic wave #Transport engineering #Transportation Planning and Optimization #physics.flu-dyn #physics.soc-ph
paper · pdf · doi:10.1088/1742-5468/2008/04/p04019
published in Journal of Statistical Mechanics Theory and Experiment 2008(04), P04019 (Institute of Physics)
arxiv created 2008/02/05 · openalex publication_date 2008/04/16 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
Based on fluid-dynamic and many-particle (car-following) simulations of traffic flows in (urban) networks, we study the problem of coordinating incompatible traffic flows at intersections. Inspired by the observation of self-organized oscillations of pedestrian flows at bottlenecks, we propose a self-organization approach to traffic light control. The problem can be treated as a multi-agent problem with interactions between vehicles and traffic lights. Specifically, our approach assumes a priority-based control of traffic lights by the vehicle flows themselves, taking into account short-sighted anticipation of vehicle flows and platoons. The considered local interactions lead to emergent coordination patterns such as 'green waves' and achieve an efficient, decentralized traffic light control. While the proposed self-control adapts flexibly to local flow conditions and often leads to non-cyclical switching patterns with changing service sequences of different traffic flows, an almost periodic service may evolve under certain conditions and suggests the existence of a spontaneous synchronization of traffic lights despite the varying delays due to variable vehicle queues and travel times. The self-organized traffic light control is based on an optimization and a stabilization rule, each of which performs poorly at high utilizations of the road network, while their proper combination reaches a superior performance. The result is a considerable reduction not only in the average travel times, but also of their variation. Similar control approaches could be applied to the coordination of logistic and production processes.